RANDOM NUMBER GENERATION USING K-VECTOR Conference Paper

abstract

• This work focuses on random number generation with any prescribed nonlinear distribution using the k-vector methodology. Two approaches are introduced. The first is based on inverse transform sampling using an optimal k-vector to generate the numbers by the inversion of the cumulative distribution. The second generates samples using random searching in a pre-generated large database built by massive inversion of the prescribed nonlinear distribution using the kvector.

authors

• Mortari, Daniele

published proceedings

• SPACEFLIGHT MECHANICS 2017, PTS I - IV

author list (cited authors)

• Arnas, D., & Mortari, D.

complete list of authors

• Arnas, David||Mortari, Daniele

publication date

• January 2017

published in

• Spaceflight Mechanics 2005, Vol 120, Pts 1 and 2  Journal

International Standard Book Number (ISBN) 13

• 978-0-87703-637-1

start page

• 4109

end page

• 4124

volume

• 160